Remote Health Data Scientist: Causal Inference & Research

School of Medicine; United States; Remote; USD 90,000 - 120,000; Full time

Job summary

School of Medicine seeks a researcher to join the Pascal Geldsetzer group, focusing on econometric analyses of large public datasets. The role is remote eligible and emphasizes causal inference using quasi-experimental methods.

Responsibilities include carrying out data analyses, mentoring students, publishing in high-impact journals, and assisting with grant writing, while collaborating with funders and data providers in a diverse health research environment.

Qualifications

• Doctoral degree with quantitative training or research experience.
• Training and experience in quasi-experimental techniques (regression discontinuity, difference-in-differences, interrupted time-series, etc.).
• A background in health-related research is a plus but not required.

Responsibilities

• Carrying out data analyses
• Supervising data analyses led by graduate students and postdoctoral fellows
• Writing manuscripts for publication in scientific journals
• Mentoring and advising junior researchers
• Assisting with, and leading the writing of, grant applications for research funding
• Communicating with research funders, data providers, and project administrative staff

Skills

R

Stata

Statistical software

Education

Doctoral degree with quantitative training

Job description

School of Medicine seeks a researcher to join the Pascal Geldsetzer group, focusing on econometric analyses of large public datasets. The role is remote eligible and emphasizes causal inference using quasi-experimental methods.

Responsibilities include carrying out data analyses, mentoring students, publishing in high-impact journals, and assisting with grant writing, while collaborating with funders and data providers in a diverse health research environment.